Pith. sign in

Paper Citation Record · LEDGER

TeLL-Drive: Enhancing Autonomous Driving with Teacher LLM-Guided Deep Reinforcement Learning

As of 15 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 3 inbound Pith citation observations for arXiv:2502.01387.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2502.01387 v3

Coverage vector

measured 37 of 37 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T15:32:47.798000Z

measured 40 of 40 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:24:29.920226Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-19T04:12:59.601892Z

Reference resolution

37 of 37 outbound references displayed

  • verified exact1
  • verified fuzzy18
  • unresolved18
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 9dd55264-7cce-4c7a-8402-a57b1e5bb506 · outbound

This paper cites Milestones in autonomous driving and intelligent vehicles: Survey of surveys.

TeLL-Drive: Enhancing Autonomous Driving with Teacher LLM-Guided Deep Reinforcement Learning Milestones in autonomous driving and intelligent vehicles: Survey of surveys

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-09T15:32:47.152150Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T15:32:47.152150Z digest=sha256:8aea8118af606a5d00bba1f88169c1fee39430bc26d3ef46a696c563433bff45

Observation a05e9892-c22c-47ca-89b3-28ccea3a0aca · outbound

This paper cites A survey of end-to-end driving: Architectures and training methods.

TeLL-Drive: Enhancing Autonomous Driving with Teacher LLM-Guided Deep Reinforcement Learning A survey of end-to-end driving: Architectures and training methods

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T15:32:48.851181Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-09T15:32:47.157852Z digest=sha256:ba437f27c4aa9a7c605f32b30225e0130c6420ee6ae40a5dc5943f07f98d2aaf

Observation 9716cfdc-aef6-4d9a-9889-978e2efac90c · outbound

This paper cites Survey of deep reinforcement learning for motion planning of autonomous vehicles.

TeLL-Drive: Enhancing Autonomous Driving with Teacher LLM-Guided Deep Reinforcement Learning Survey of deep reinforcement learning for motion planning of autonomous vehicles

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T15:32:48.830625Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-09T15:32:47.171961Z digest=sha256:7f9fed113054196d2d995537383fb0d5987df23d86fc08553fe03e28500c9960

Observation 2f5643e2-cd48-4c20-8176-e149abfba87c · outbound

This paper cites Deep reinforcement learning for intelligent transportation systems: A survey.

TeLL-Drive: Enhancing Autonomous Driving with Teacher LLM-Guided Deep Reinforcement Learning Deep reinforcement learning for intelligent transportation systems: A survey

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T15:32:48.811813Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-09T15:32:47.199943Z digest=sha256:4d6c31392a83f52dbec698c3ba4d48e197159036d3adc97853f10e3fba1e48bb

Observation 64d7ba2b-ebfd-4d62-954e-f7fb5b9e1c8e · outbound

This paper cites Mtd- gpt: A multi-task decision-making gpt model for autonomous driving at unsignalized intersections.

TeLL-Drive: Enhancing Autonomous Driving with Teacher LLM-Guided Deep Reinforcement Learning Mtd- gpt: A multi-task decision-making gpt model for autonomous driving at unsignalized intersections

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T15:32:48.795599Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-09T15:32:47.253759Z digest=sha256:1d2674396b11048fb51532b495d0e5153cb62bcc5419ee74b674793fe9ea4122

Observation cfd9efa2-15a3-4b2d-ac73-1aa048226df4 · outbound

This paper cites Decision making of autonomous vehicles in lane change scenarios: Deep reinforcement learning approaches with risk awareness.

TeLL-Drive: Enhancing Autonomous Driving with Teacher LLM-Guided Deep Reinforcement Learning Decision making of autonomous vehicles in lane change scenarios: Deep reinforcement learning approaches with risk awareness

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T15:32:48.778046Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-09T15:32:47.297200Z digest=sha256:96897f4ac92ea0bc740b0b240f7df371ecae92cc45fbcb039c0dce0c11b60925

Observation 2aa94618-d0af-440b-a6b8-5cc2b3f869d1 · outbound

This paper cites Automatically generated curriculum based reinforcement learning for autonomous vehicles in urban environment.

TeLL-Drive: Enhancing Autonomous Driving with Teacher LLM-Guided Deep Reinforcement Learning Automatically generated curriculum based reinforcement learning for autonomous vehicles in urban environment

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T15:32:48.760486Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-09T15:32:47.333676Z digest=sha256:a86f81bc08b01afec7fade746bf8ce80f6563eb0ddf7497cdf88c2fa324bed93

Observation 5a4c91ca-18f7-4510-9cfe-9a168589c8cd · outbound

This paper cites Cooperation-aware reinforcement learning for merging in dense traffic.

TeLL-Drive: Enhancing Autonomous Driving with Teacher LLM-Guided Deep Reinforcement Learning Cooperation-aware reinforcement learning for merging in dense traffic

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-09T15:32:47.355455Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T15:32:47.355455Z digest=sha256:e3eef73544d23f028eedd061495bf13660c1b5255cccbb5c2d54a9493f9c4ede

Observation c7c9f0ec-4ca7-4c5e-9c62-0e8253226d8a · outbound

This paper cites Formulation of deep reinforcement learning architecture toward autonomous driving for on-ramp merge.

TeLL-Drive: Enhancing Autonomous Driving with Teacher LLM-Guided Deep Reinforcement Learning Formulation of deep reinforcement learning architecture toward autonomous driving for on-ramp merge

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T15:32:48.733305Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-09T15:32:47.360048Z digest=sha256:060cfcf6a58bb5aa7fed5fedaa0e3bd81a2133a16be0724e7b04e1c701366115

Observation 81181629-bcfe-4b44-9b55-aeca5ad8c1aa · outbound

This paper cites Deep reinforcement learning for autonomous driving: A survey.

TeLL-Drive: Enhancing Autonomous Driving with Teacher LLM-Guided Deep Reinforcement Learning Deep reinforcement learning for autonomous driving: A survey

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T15:32:48.716917Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-09T15:32:47.364451Z digest=sha256:57afc331493a904b60efd77bf876af980c066f0a7e1e48b51789c9517756af16

Observation e0c72b31-de34-49c4-b86e-197ad2ed81f9 · outbound

This paper cites GPT-4o System Card.

TeLL-Drive: Enhancing Autonomous Driving with Teacher LLM-Guided Deep Reinforcement Learning GPT-4o System Card

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-09T15:32:47.368954Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T15:32:47.368954Z digest=sha256:48b02350c6dfa0bd4a1196f3d2bbec8bead194871fee2a23c20328125af8b100

Observation 1708a841-88ed-4ba8-a1d7-5bde8e73b94c · outbound

This paper cites Llm4drive: A survey of large language models for autonomous driving.

TeLL-Drive: Enhancing Autonomous Driving with Teacher LLM-Guided Deep Reinforcement Learning Llm4drive: A survey of large language models for autonomous driving

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T15:32:48.674726Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-09T15:32:47.375575Z digest=sha256:839747800230f6b0dcf4bf1f89e2794f7217425cd3647df82afb0adbd6457864

Observation f9799add-458c-4afa-8f06-9b94c6bb0190 · outbound

This paper cites A survey on multimodal large language models for autonomous driving.

TeLL-Drive: Enhancing Autonomous Driving with Teacher LLM-Guided Deep Reinforcement Learning A survey on multimodal large language models for autonomous driving

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-09T15:32:47.379887Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T15:32:47.379887Z digest=sha256:aae516d60d663467df42b19957ffd1b48c034534980a5aa00119ae6f37b5db79

Observation e0bd28e2-0cab-4bee-82c6-aae32894adb2 · outbound

This paper cites Drivegpt4: Inter- pretable end-to-end autonomous driving via large language model.

TeLL-Drive: Enhancing Autonomous Driving with Teacher LLM-Guided Deep Reinforcement Learning Drivegpt4: Inter- pretable end-to-end autonomous driving via large language model

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T15:32:48.593825Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-09T15:32:47.384159Z digest=sha256:a0eef9ec70d3f313bed7400b47837bc10a1f568e5516c8e1e9742ffe957b40a0

Observation 1ed7dfe5-cb8f-4b47-bf50-ba9c962c32e5 · outbound

This paper cites Drivellm: Charting the path toward full autonomous driving with large language models.

TeLL-Drive: Enhancing Autonomous Driving with Teacher LLM-Guided Deep Reinforcement Learning Drivellm: Charting the path toward full autonomous driving with large language models

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T15:32:48.533213Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-09T15:32:47.388583Z digest=sha256:4fe1e6bb716192aba70be9c79097e0dbc5638c7b6e5d43ef70ef8401dac5f158

Observation b66a7362-5dee-4d77-a941-e9963bbe5c7c · outbound

This paper cites Cooperative decision-making for cavs at unsignalized intersections: A marl approach with attention and hierarchical game priors.

TeLL-Drive: Enhancing Autonomous Driving with Teacher LLM-Guided Deep Reinforcement Learning Cooperative decision-making for cavs at unsignalized intersections: A marl approach with attention and hierarchical game priors

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T15:32:48.462313Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-09T15:32:47.393167Z digest=sha256:a37be4dda9d5dd256aac1139b4c8b92716d31f2857bd4d39ebc8ed808722083d

Observation 6b3677b4-de4e-45ce-9d71-9435dfdde126 · outbound

This paper cites A reinforcement learning approach to autonomous decision making of intelligent vehicles on highways.

TeLL-Drive: Enhancing Autonomous Driving with Teacher LLM-Guided Deep Reinforcement Learning A reinforcement learning approach to autonomous decision making of intelligent vehicles on highways

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T15:32:48.437159Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-09T15:32:47.397299Z digest=sha256:5910300dd4c10d25e866bc1611ad9a35ab593579d837003fa825b1b0f1a5bf8a

Observation 21345b95-8157-4921-a667-2da2d66135fd · outbound

This paper cites Proximal Policy Optimization Algorithms.

TeLL-Drive: Enhancing Autonomous Driving with Teacher LLM-Guided Deep Reinforcement Learning Proximal Policy Optimization Algorithms

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-09T15:32:47.401380Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T15:32:47.401380Z digest=sha256:2ccb754353e59192b45f9212665805e8872a341509cc0f85b1a279ebc0166892

Observation 1f9995f5-ff47-4241-b075-0dffa0b6346b · outbound

This paper cites Playing Atari with Deep Reinforcement Learning.

TeLL-Drive: Enhancing Autonomous Driving with Teacher LLM-Guided Deep Reinforcement Learning Playing Atari with Deep Reinforcement Learning

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-09T15:32:47.406469Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T15:32:47.406469Z digest=sha256:1621afb22784f067bc0f14f1d0be5b742492d7be570b06deed59df48e6873942

Observation 2c845b82-e7df-489f-823e-95f468d40a19 · outbound

This paper cites A survey of deep rl and il for autonomous driving policy learning.

TeLL-Drive: Enhancing Autonomous Driving with Teacher LLM-Guided Deep Reinforcement Learning A survey of deep rl and il for autonomous driving policy learning

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-09T15:32:47.411764Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T15:32:47.411764Z digest=sha256:237021730ceac8570a11a3147b1557c7f92f632a1917571b83b46e9419a4c6e7

Observation 89537664-88ad-461c-95a2-3f24e01b8584 · outbound

This paper cites Aligning Large Multimodal Models with Factually Augmented RLHF.

TeLL-Drive: Enhancing Autonomous Driving with Teacher LLM-Guided Deep Reinforcement Learning Aligning Large Multimodal Models with Factually Augmented RLHF

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-09T15:32:47.416758Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T15:32:47.416758Z digest=sha256:dd514d1df07aac3eef84ec47a23808e2a5a13d537eed5120606ba7d31fdbcc6f

Observation f46c1dc0-6a0a-4e34-99d7-73d578566df3 · outbound

This paper cites Rlhf-v: Towards trustworthy mllms via behavior alignment from fine- grained correctional human feedback.

TeLL-Drive: Enhancing Autonomous Driving with Teacher LLM-Guided Deep Reinforcement Learning Rlhf-v: Towards trustworthy mllms via behavior alignment from fine- grained correctional human feedback

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T15:32:48.409442Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-09T15:32:47.421491Z digest=sha256:8d3651eeca3960a151e7df6c81b284c10d06d83081bbff6b978a69d8394520f3

Observation cc861c97-7743-4a95-8fe8-7c01c386f401 · outbound

This paper cites Towards interactive and learnable cooperative driving automation: a large language model-driven decision-making framework.

TeLL-Drive: Enhancing Autonomous Driving with Teacher LLM-Guided Deep Reinforcement Learning Towards interactive and learnable cooperative driving automation: a large language model-driven decision-making framework

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-09T15:32:47.426231Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T15:32:47.426231Z digest=sha256:3d7a666d462c24d8c9232d51574ef9737f2fe6023e91cdc211700c497852a7bc

Observation 114e9595-d9b9-4681-89ad-4120a37d3135 · outbound

This paper cites LanguageMPC: Large Language Models as Decision Makers for Autonomous Driving.

TeLL-Drive: Enhancing Autonomous Driving with Teacher LLM-Guided Deep Reinforcement Learning LanguageMPC: Large Language Models as Decision Makers for Autonomous Driving

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-09T15:32:47.430986Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T15:32:47.430986Z digest=sha256:19f9ba441495ec4eb5150a1a44a12230dfeace86dae277b8b9761adefd723fc3

Observation 473a9fc8-e6f9-4d52-bce8-e9a224567fc2 · outbound

This paper cites Drive like a human: Rethinking autonomous driving with large language models.

TeLL-Drive: Enhancing Autonomous Driving with Teacher LLM-Guided Deep Reinforcement Learning Drive like a human: Rethinking autonomous driving with large language models

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-09T15:32:47.436262Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T15:32:47.436262Z digest=sha256:8e80b335c6c7f1105cfb74a0ba277c8b6aff7c0282bcac09e2c0eef3503dff97

Observation e096bb22-b76f-4c7d-ae22-529a61b30b45 · outbound

This paper cites DiLu: A Knowledge-Driven Approach to Autonomous Driving with Large Language Models.

TeLL-Drive: Enhancing Autonomous Driving with Teacher LLM-Guided Deep Reinforcement Learning DiLu: A Knowledge-Driven Approach to Autonomous Driving with Large Language Models

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-09T15:32:47.440437Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T15:32:47.440437Z digest=sha256:398491fa8ee505c16011d2a419ad62f713f2b8c2f8e61f71fd1f3da1b5f9f612

Observation b84cf42e-8172-48f9-801e-6deaed7927d3 · outbound

This paper cites Language-Driven Policy Distillation for Cooperative Driving in Multi-Agent Reinforcement Learning.

TeLL-Drive: Enhancing Autonomous Driving with Teacher LLM-Guided Deep Reinforcement Learning Language-Driven Policy Distillation for Cooperative Driving in Multi-Agent Reinforcement Learning

Reference 27

Resolution
verified exact
local_arxiv, observed 2026-08-09T15:32:47.912074Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-09T15:32:47.445308Z digest=sha256:70dbd5c9fee3b76a3919151949b05a06daecdc561c71c949e7508ce173b8f9e7

Observation 03215456-93e2-473a-8a9b-488b68c66eff · outbound

This paper cites Large language models are semi-parametric reinforcement learning agents.

TeLL-Drive: Enhancing Autonomous Driving with Teacher LLM-Guided Deep Reinforcement Learning Large language models are semi-parametric reinforcement learning agents

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T15:32:48.381935Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-09T15:32:47.452330Z digest=sha256:926861e74ac4b9a6a73dc8effdb1a8b54874bf2a18457327c415f647e6fa205e

Observation e061537a-bd39-4d31-ad0e-3ed019efe6f4 · outbound

This paper cites AutoML-Agent: A Multi-Agent LLM Framework for Full-Pipeline AutoML.

TeLL-Drive: Enhancing Autonomous Driving with Teacher LLM-Guided Deep Reinforcement Learning AutoML-Agent: A Multi-Agent LLM Framework for Full-Pipeline AutoML

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-09T15:32:47.489140Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T15:32:47.489140Z digest=sha256:823d466e33f7ed2ab4bd43520921cef324b18cf575af67b116b0fa66f31f8d89

Observation 9575502c-5eaf-4a00-879c-3b25962f2ac3 · outbound

This paper cites Eureka: Human-Level Reward Design via Coding Large Language Models.

TeLL-Drive: Enhancing Autonomous Driving with Teacher LLM-Guided Deep Reinforcement Learning Eureka: Human-Level Reward Design via Coding Large Language Models

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-09T15:32:47.536824Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T15:32:47.536824Z digest=sha256:7878ba700bfa9c9dfca65f3a705297ffa0e36ad4e2c3bd7e8b02de5990032590

Observation 80843b15-fca3-4343-aa6c-a4360840f6b4 · outbound

This paper cites Chain-of-thought prompting elicits reasoning in large language models.

TeLL-Drive: Enhancing Autonomous Driving with Teacher LLM-Guided Deep Reinforcement Learning Chain-of-thought prompting elicits reasoning in large language models

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-09T15:32:47.577070Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T15:32:47.577070Z digest=sha256:6b657e59d05d56380ab6f73958c64b36e29b759e2ff4f86f778a92cc8e1ab0b2

Observation 895c12fb-233f-4a27-8347-94720fe505c6 · outbound

This paper cites A survey of actor-critic reinforcement learning: Standard and natural policy gradients.

TeLL-Drive: Enhancing Autonomous Driving with Teacher LLM-Guided Deep Reinforcement Learning A survey of actor-critic reinforcement learning: Standard and natural policy gradients

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T15:32:48.355271Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-09T15:32:47.614779Z digest=sha256:5fc9ccc13da0838538ed5f71c7b6eb8625287e749f0bbb447a367b6fbd310ea6

Observation 6ac4e898-b3d3-4b02-aa84-92de7538977a · outbound

This paper cites Efficient deep reinforcement learning with imitative expert priors for autonomous driving.

TeLL-Drive: Enhancing Autonomous Driving with Teacher LLM-Guided Deep Reinforcement Learning Efficient deep reinforcement learning with imitative expert priors for autonomous driving

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T15:32:48.338290Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-09T15:32:47.685056Z digest=sha256:3788f23ebe8bd17618d2f5b78119f19519f478ec9f10a7b51841774b7f288904

Observation 26202bb1-3501-408e-ab03-cc3050667063 · outbound

This paper cites An environment for autonomous driving decision- making.

TeLL-Drive: Enhancing Autonomous Driving with Teacher LLM-Guided Deep Reinforcement Learning An environment for autonomous driving decision- making

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-09T15:32:47.758109Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T15:32:47.758109Z digest=sha256:e5c49ee1c4a13f0361c3c08576614b54acb7794f76ab46ecb26f1be92a5981ab

Observation b0c26e35-f012-4f53-8a5c-1ad5fc9620e7 · outbound

This paper cites Asynchronous Methods for Deep Reinforcement Learning.

TeLL-Drive: Enhancing Autonomous Driving with Teacher LLM-Guided Deep Reinforcement Learning Asynchronous Methods for Deep Reinforcement Learning

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-09T15:32:47.787354Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T15:32:47.787354Z digest=sha256:1cd8298df5811609a0c610c4437816aa46f0fe70c7e78a7d9a6121969ae3496c

Observation 95749692-a54a-4d73-9f4c-a63ba8ce0c19 · outbound

This paper cites Generalization, Mayhems and Limits in Recurrent Proximal Policy Optimization.

TeLL-Drive: Enhancing Autonomous Driving with Teacher LLM-Guided Deep Reinforcement Learning Generalization, Mayhems and Limits in Recurrent Proximal Policy Optimization

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-09T15:32:47.793071Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T15:32:47.793071Z digest=sha256:6471c88032a419aa201519bfb7ccc21a82b67bc648321458f704cbc6cb5b0aee

Observation 9122a6c7-76c9-4962-8ba6-419e4ed42e44 · outbound

This paper cites Modeling and simulation of merging behavior at urban expressway on-ramp.

TeLL-Drive: Enhancing Autonomous Driving with Teacher LLM-Guided Deep Reinforcement Learning Modeling and simulation of merging behavior at urban expressway on-ramp

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T15:32:48.308884Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-09T15:32:47.798000Z digest=sha256:29a7de61ab9c6e06038e7339eaaea3ae1fbb07991a7977cc14f63355b83f4a7d

Pith citing papers

Observation f614df40-4701-4c5d-81b0-cadd7a2005d9 · inbound

LeAD: The LLM Enhanced Planning System Converged with End-to-end Autonomous Driving cites this paper.

LeAD: The LLM Enhanced Planning System Converged with End-to-end Autonomous Driving TeLL-Drive: Enhancing Autonomous Driving with Teacher LLM-Guided Deep Reinforcement Learning

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-06T19:24:29.920226Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:24:29.920226Z digest=sha256:ae181a2a5b18e7845cf6a0e99bcf2b13a11bf924610bec3c00d652b47b8d5b73

Observation c9d23c76-3c9b-4e32-bb3a-b84d65391bc9 · inbound

LLM-Enhanced Multi-Agent Reinforcement Learning with Expert Workflow for Real-Time P2P Energy Trading cites this paper.

LLM-Enhanced Multi-Agent Reinforcement Learning with Expert Workflow for Real-Time P2P Energy Trading TeLL-Drive: Enhancing Autonomous Driving with Teacher LLM-Guided Deep Reinforcement Learning

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-05-19T04:12:59.604856Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-19T04:12:42.574595Z digest=sha256:5b436a70d9c461b9f75605ebe6030e22ad737da503d954f54eec6456a4a6a83b

Observation 93bfc94a-812d-4cd5-9584-34e9027f3292 · inbound

A Survey on the Applications of Generative Artificial Intelligence in Automated Driving Systems Test Scenario Generation Methods cites this paper.

A Survey on the Applications of Generative Artificial Intelligence in Automated Driving Systems Test Scenario Generation Methods TeLL-Drive: Enhancing Autonomous Driving with Teacher LLM-Guided Deep Reinforcement Learning

Reference 96

Resolution
unresolved
no resolver link, observed 2026-08-03T15:54:39.843021Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T15:54:39.843021Z digest=sha256:32c23ec3fd5f6dd57df0d3ceaf8f1ee520e7cfc76cc3550b1243161b49abddfa